Fault Classification Model of Rotor Based on Support Vector Machine
The vibration signals of rotating machinery in operation consist of plenty of information about its running condition, and extraction and identification of fault signals in the process of speed change are necessary for the fault diagnosis of rotating machinery. This paper improves DDAG classification method and proposes a new fault diagnosis model based on support vector machine to solve the problem of restricting the rotating machinery fault intelligent diagnosis due to the lack of fault data samples. The testing results demonstrate that the model has good classification precision and can correctly diagnose faults.
W. Niu et al., "Fault Classification Model of Rotor Based on Support Vector Machine", Applied Mechanics and Materials, Vols. 66-68, pp. 1982-1987, 2011